Research was conducted on motorcycling and alcohol-impaired motorcycling in Hawaii to develop a crash typology. The investigation expanded the scope of rider characteristics analysis by examining the combined effects on motorcycle crashes of rider behavior (helmet use, speeding, actions taken before a crash, etc.), environmental factors (urban versus rural locations, roadway alignment, etc.), and spatial patterns. The crash typology was used to derive logistic regression models for explaining alcohol-involved crashes, single-vehicle crashes, and injury outcomes (including fatalities) associated with motorcycle crashes. The logistic models allowed comparisons of the relative importance of various rider characteristics, temporal and environmental correlates associated with motorcycle crashes, and the associated crash types and injury outcomes. Finally, a spatial cluster analysis was also performed with both geographic information system and spatial analytical tools. The analysis suggests that overall behavioral and temporal factors are more significant predictors of alcohol-involved crash patterns than environmental or roadway features. The findings are qualified in terms of the usefulness of the methods to motorcycle safety researchers and relevance to motorcycle safety initiatives in the state of Hawaii.
Samenvatting